Calibration Methods for Brain-Computer Interfaces is a procedural framework within neuroadaptive system design that systematically adjusts the translation algorithms of brain signals into machine commands by aligning individual neural patterns with intended outputs to ensure accurate and reliable user-device interaction.
126
Publications
6.9K
Citations
416
Authors
217
Institutions
Publications per year
2017–2026
60
Parents
Publications
126
BCI Competition 2008 { Graz data set B
R. Leeb, Clemens Brunner · 2008 · 319 citations
Towards Zero Training for Brain-Computer Interfacing
Matthias Krauledat, Michael Tangermann, Benjamin Blankertz et al. · PLoS ONE · 2008 · 246 citations · Full text
1–5 of 126
Authors
416
- BB
8
h-index
- CV
7
h-index
- DW
7
h-index
- KM
7
h-index
- LR
7
h-index
1–5 of 416
Institutions
217
Technische Universität Berlin
Berlin, Germany
12 h-index
35 publications
3.3K citations
University of California San Diego
San Diego, United States
9 h-index
20 publications
792 citations
Fraunhofer Institute for Production Systems and Design Technology
Berlin, Germany
8 h-index
26 publications
2.6K citations
Institute for Infocomm Research
Singapore, Singapore
7 h-index
28 publications
1K citations
Harvard University
Cambridge, United States
7 h-index
14 publications
1.7K citations
Brown University
Providence, United States
7 h-index
38 publications
5.9K citations
Massachusetts General Hospital
Boston, United States
6 h-index
21 publications
3.5K citations
Bernstein Center for Computational Neuroscience Berlin
Berlin, Germany
6 h-index
9 publications
927 citations
1–8 of 217
Venues
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
16 publications · 1K citations
16
h-index
- Journal of Neural Engineering
14 publications · 852 citations
14
h-index
- IEEE Transactions on Biomedical Engineering
11 publications · 614 citations
11
h-index
- Frontiers in Neuroscience
8 publications · 288 citations
8
h-index
- PLoS ONE
6 publications · 582 citations
6
h-index
1–5